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Enregistrement W4414618230 · doi:10.1111/1460-6984.70125

Sentence Comprehension and L2 Exposure Effects in 6‐Year‐Old Sequentially Bilingual Children With Typical Development and Developmental Language Disorder

2025· article· en· W4414618230 sur OpenAlexaff
Sini Smolander, Marja Laasonen, Pekka Lahti‐Nuuttila, Eva Arkkila, Elin Thordardottir, Sari Kunnari

Notice bibliographique

RevueInternational Journal of Language & Communication Disorders · 2025
Typearticle
Langueen
DomainePsychology
ThématiqueLanguage Development and Disorders
Établissements canadiensMcGill UniversityMcGill University Health Centre
Organismes subventionnairesEmil Aaltosen SäätiöKela
Mots-clésComprehensionSentenceLanguage developmentLanguage assessmentNeuroscience of multilingualismTest (biology)Language disorderSecond-language attritionLanguage acquisition

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Differentiating typical language development (TD) and developmental language disorder (DLD) in a bilingual context is difficult. The societal language is often the only mutual language of the child and the SLT. It has been shown that when assessing second language (L2) performance using tools developed for monolingual children, substantial differences between typical and disordered development can be found. There is a need for a systematic understanding of the applicability of tests across different language domains, taking language exposure into account. Sentence comprehension is an important part of language development, and receptive difficulties have often been considered to have prognostic value. Yet, the diagnostic value of sentence comprehension has received little research attention. AIM: In the Helsinki longitudinal SLI study (HelSLI), we investigated L2 exposure effects on sentence comprehension in sequentially bilingual typically developing children (BiTD) and bilingual children with DLD (BiDLD). In addition to group-level comparisons, we examined the classification accuracy of two L2 sentence comprehension tests, taking several explanatory factors into account. METHODS AND PROCEDURES: A total of 100 six-year-old children were recruited from day care centres and a hospital clinic (54 BiTD children and 46 bilingual children with DLD). Two offline tests with multiple-choice and act-out tasks (Sentence Comprehension Test (Lausetesti) and Reynell Developmental Language Scales III, Verbal Comprehension Scale) were used to investigate sentence-level comprehension in Finnish. Multiple regression analysis was used to compare BiTD and BiDLD group performance while considering the effects of relative lifetime exposure to L2. Covariate-specific receiver operating characteristic (ROC) analysis was used to study the classification accuracy of the two tests and estimate the thresholds for optimal sensitivity and specificity of the tests. OUTCOMES AND RESULTS: The TD bilingual children performed significantly better than their peers with DLD in both sentence comprehension tests. The effect of L2 exposure was significant but small and affected both groups similarly. Both tests classified the groups with fair sensitivity and specificity at their best, but the accuracy depended greatly on exposure. Depending on the age and exposure to L2, a sensitivity of 0.80 yielded a specificity of 0.16-0.87 on the Sentence Comprehension Test and a specificity of 0.19-0.87 on the RDLS III Verbal Comprehension Scale. CONCLUSIONS AND IMPLICATIONS: Sentence comprehension in L2 is promising in informing the detection of language difficulties in L2 Finnish learners with several first-language backgrounds. However, interpretation must take L2 exposure into account. In addition, no one assessment tool or domain can be considered enough for the identification of DLD. In the future, the importance of sentence comprehension tests as classifiers should be considered as part of a larger assessment battery. WHAT THIS PAPER ADDS: What is already known on this subject Differentiating developmental language disorder (DLD) from typical language development (TD) is difficult in bilingual children. Assessment tools are needed for more reliable detection of disordered development. It has been shown that assessing both languages in bilingual children adds to the classification accuracy. The societal language is, however, often the only mutual language between the SLT and the child, and the only available tests are frequently in the child's L2. It has been found that substantial differences in second language (L2) performance between bilingual typically developing children (BiTD) and bilingual children with DLD (BiDLD) groups can be found in different language domains. Language exposure effects in BiTD and BiDLD children as well as classification accuracy of the L2 tests vary, however. What this paper adds to existing knowledge L2 sentence comprehension has received little attention in the field of communication disorders. In the current study, sentence comprehension tests showed substantial differences in L2 performance between bilingual TD and DLD children. On a group level, the effect of L2 exposure was small relative to some other language domains and appeared similar in BiTD and BiDLD children. Classification accuracy, however, depended greatly on exposure. In addition, it was found that some tests classify the children with more exposure better and some those with less exposure. Such patterns are related to the difficulty of the test items and the age range targeted by each test. What are the potential or actual clinical implications of this work? Sentence comprehension is a promising language domain informing the identification of DLD in bilingual children with different L1 backgrounds. Even though the BiTD and BiDLD groups differ significantly in their test performance, it is advisable to consider the possible differences in sensitivity and specificity of the test depending on exposure. In the domain of sentence comprehension, despite the persistent difference in performance between BiTD and BiDLD children, DLD children seem to be able to benefit from the exposure in a similar manner as TD children instead of lagging behind in the course of accumulating exposure.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,171
Score d'incertitude au seuil0,684

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,006
Tête enseignante GPT0,285
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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